Multi Histogram Equalization Based Contrast Enhancement for Images

The fundamental and important pre-processing stage in image processing is the image contrast enhancement technique. Histogram equalization is an effective contrast enhancement technique and thus in this paper, a histogram equalization based technique called Quadrant Dynamic with Automatic Plateau Limit Histogram Equalization (QDAPLHE) is introduced. In this method, a hybrid of dynamic and clipped histogram equalization methods are used to increase the brightness preservation and to reduce the over enhancement. Initially, the proposed QDAPLHE algorithm passes the input image through a Decision based modified median filter (DBMMF) to remove the noises present in the image. Then the histogram of the filtered image is divided into four sub histograms while maintaining second separated point as the mean brightness. Next, the clipping process is implemented by calculating automatically the plateau limit as the clipped level. The clipped portion of the histogram is modified to reduce the loss of image intensity value. Finally, the clipped portion is redistributed uniformly to the entire dynamic range and the conventional histogram equalization is executed in each sub-histogram independently. Hence, the contrast enhancement is improved and the noise amplifying artifacts are reduced. Based on the qualitative and the quantitative analysis, the QDAPLHE method outperforms compared to some existing methods in literature.